Devices, systems, and methods for mobile personal emergency response services

ABSTRACT

This disclosure describes systems, methods, and devices for mobile personal emergency response services. A wearable device may receive a model from a second device. The model may include an event criterion. The wearable device may determine data indicative of an event associated with a user. The wearable device may determine, based on a comparison of the data to the model, an occurrence of the event. The wearable device may initiate, based on the occurrence of the event, a communication session with a third device.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.62/874,335, filed Jul. 15, 2019, which is incorporated by reference inits entirety.

BACKGROUND

Wireless devices are becoming widely prevalent and are increasinglybeing used for different forms of communication with a variety ofdevices. However, to conserve resources such as power, some devices relyon other devices to evaluate data and send messages. In some situations,such as medical emergencies, one device's reliance on other devices mayresult in latency that may undermine user experience. Therefore, thereis a need for enhanced systems and methods of communication, and forimproved device designs.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example system for mobile personal emergencyresponse services using devices, in accordance with one or more exampleembodiments of the present disclosure.

FIG. 2 illustrates a block diagram of a wearable device for use inmobile personal emergency response services, in accordance with one ormore example embodiments of the present disclosure.

FIG. 3 illustrates an example system for enabling emergency responseservices, in accordance with one or more example embodiments of thepresent disclosure.

FIG. 4 illustrates a functional diagram of an exemplary device for usein mobile personal emergency response services, in accordance with oneor more example embodiments of the present disclosure.

FIG. 5 illustrates a functional diagram of an exemplary device for usein mobile personal emergency response services, in accordance with oneor more example embodiments of the present disclosure.

FIG. 6 illustrates a functional diagram of an exemplary device for usein mobile personal emergency response services, in accordance with oneor more example embodiments of the present disclosure.

FIG. 7A illustrates an exemplary device for use in mobile personalemergency response services, in accordance with one or more exampleembodiments of the present disclosure.

FIG. 7B illustrates a cross-section of the device band of the device ofFIG. 7A, in accordance with one or more example embodiments of thepresent disclosure.

FIG. 7C illustrates an exemplary device for use in mobile personalemergency response services, in accordance with one or more exampleembodiments of the present disclosure.

FIG. 7D illustrates a cross-section of the device band of the device ofFIG. 7C, in accordance with one or more example embodiments of thepresent disclosure.

FIG. 8 illustrates a flow diagram of an illustrative process forenabling emergency response services, in accordance with one or moreexample embodiments of the present disclosure.

FIG. 9 illustrates a block diagram of an example of a machine, inaccordance with one or more example embodiments of the presentdisclosure.

Certain implementations will now be described more fully below withreference to the accompanying drawings, in which various implementationsand/or aspects are shown. However, various aspects may be implemented inmany different forms and should not be construed as limited to theimplementations set forth herein; rather, these implementations areprovided so that this disclosure will be thorough and complete, and willfully convey the scope of the disclosure to those skilled in the art.Like numbers in the figures refer to like elements throughout. Hence, ifa feature is used across several drawings, the number used to identifythe feature in the drawing where the feature first appeared will be usedin later drawings.

DETAILED DESCRIPTION Overview

Example embodiments described herein provide certain systems, methods,and devices for mobile personal emergency response services.

Devices, including wearable devices, may be used to detect events, suchas when a person falls or experiences a change in health conditions(e.g., heartrate, blood sugar, electrocardiogram,respiration/oxygenation, and the like), with appropriate user consentand in accordance with applicable laws and regulations. For example, awearable device such as a watch, band, belt, smart glasses, smart rings,bracelets, or other type of device may facilitate personal emergencyresponse service communications by identifying a condition of the deviceuser, and communicating with other devices to initiate emergency orother services. In particular, some wearable devices rely on other typesof devices (e.g., non-wearable devices) to analyze data and to initiatecommunication sessions, such as phone calls, messages, and the like, onbehalf of the wearable devices.

Some devices, such as wearable devices, may be limited in size, therebylimiting physical space for hardware, such as batteries or other powersources. Due to limited battery size, for example, some devicesoutsource operations, such as calculations and sending ofcommunications, to other devices to conserve the limited power supply(e.g., battery life) of the wearable device. For example, some wearabledevices pair with other devices that initiate phone calls and/or performcalculations on behalf of a wearable device. Some wearable devices senddata to a network-based (e.g., cloud-based) device for processing.However, outsourcing of calculations and messaging may result inlatency/delay as the wearable device waits for another device to performoperations (e.g., delay compared to the wearable device performing anaction itself). Relying on another device to perform operations mayinvolve reliance on a connection between devices. In an emergencysituation, such as a medical emergency, latency/delay may be thedifference between saving a person's life or failing to save a person'slife. For example, when a connection between a wearable device andanother device is poor or disconnected, life-saving calculations andresponses may be delayed or may not occur. Even when a connectionbetween devices is strong, the delay caused by sending data and waitingfor another device to initiate communications on behalf of the wearabledevice may result in costly delays. As such, some devices may benefitfrom faster calculations and initiations of communications performed bythe devices themselves (e.g., rather than outsourcing operations toother devices).

Because the local performance of operations on a battery-powered devicemay result in a faster use of a battery's power supply, devices thatperform operations locally (e.g., in contrast with outsourcingoperations to another device) may benefit from maximizing battery sizebased on size limitations (e.g., a size of wearable watch device).However, even the largest batteries that may fit into a wearable device,such as a smart watch, may require frequent (e.g., daily) charging dueto the local performance of operations. As such, some devices maybenefit from enhanced designs that allow for more battery power withoutincreasing the size of the devices.

Therefore, devices and device users may benefit from localized eventdetection and from improved power performance.

In one or more embodiments, a device may identify events, such asmedical emergencies, based on local (e.g., on-device) analysis of dataassociated with a device user. For example, the device may analyze oneor more of device data (e.g., accelerometer or other motion data) andbiometric data (e.g., heart rate data, blood pressure data, bloodglucose data, breathing data, etc.) for the detection of an event suchas fall (e.g., the motion data of the device may indicate that a personwearing/holding the device fell down), a cardiac event, or other type ofmedical emergency. To identify the event locally at the device, thedevice may compare device and/or biometric data to a model determined byand received from another device (e.g., a cloud-based device or othertype of device). The model may provide criteria, such as datathresholds, data profiles, etc., that indicate whether device and/orbiometric data is indicative of the occurrence of an event. The devicemay compare device and/or biometric data to the criteria of the model todetermine whether any detected motion and/or biometric data indicatesthe occurrence of an event.

In one or more embodiments, to respond quickly to a detected event, thedevice may initiate one or more communications, such as phone calls(e.g., using cellular, Wi-Fi, LTE, etc.), to one or more other devices,such as emergency call centers, medical professionals, family members,caregivers, and the like. For example, the device may have cellularand/or Wi-Fi communication capability to facilitate phone calls executedusing the device (e.g., rather than relying on another device, such as aBluetooth-paired device, to execute the phone call).

In one or more embodiments, to improve the power performance of a watchdevice that performs event detection locally, at least a portion of thewatch device's power supply and/or communication hardware may be housedin the watch band (e.g., instead of within the watch face). For example,one or more batteries and/or antennae may be stored in the band of thewatch device, thereby allowing the face of the watch device to storeother hardware, and allowing the power supply to be increased (e.g., alarger battery). In one or more embodiments, a combination of one ormore power sources, antennas, and/or sensors may be incorporated into awatch band of a watch device (or band of another device securing thedevice to a person). For example, the band may use a combination of oneor more flexible batteries, one or more antennas, and one or moresensors capable of integrating into a link band or various types ofstrap bands. Such a configuration may allow for a smaller device (e.g.,watch face) or other hardware within the watch device, and may improvereception of the antennas (e.g., by using shielding between the batteryand antennas). The interchangeability may provide consumers with moreoptions, and the use of some types of bands (e.g., links) may allow forincreased power capability (e.g., adding links with more power storagemay add to existing power storage of a band).

In one or more embodiments, a watch device with a screen for presentingmultiple user interfaces may be interchangeable with the watch band. Thesize of the screen may be minimized to reduce power consumption and tosimplify the device for users. The device may have one or more sensorscapable of detecting user data, such as heartrate, device accelerometerdata, body and/or device temperature data, device gyroscopic data,electrocardiogram data, and/or other data. The sensors may be in thedetachable device and/or in the detachable band. The device may operablyconnect to the band using one or more connection mechanisms, such asmagnets, clasps, adhesives, interconnecting surfaces, and the like.Using sensor data detected by the one or more sensors, the device maydetect an event based on comparisons of the sensor data to the model.

In one or more embodiments, the watch device and/or a remote computingnetwork (e.g., cloud network) may perform analysis on data detected bythe one or more sensors to determine whether a person has fallen (e.g.,based on accelerometer, magnetometer, and/or gyroscope data) and/orwhether the person is having an emergency health event (e.g., heartattack, blood sugar incident, hyperventilation, or some other event).For example, the one or more sensors may detect device data and/orbiometric data. The device data may detect motion (e.g., translation,rotation, or the like) and/or location information associated with aperson wearing the watch device. The biometric data, such as heart rate(HR), breathing rate, pulse oximetry, body fat, hydration level, bodytemperature, blood sugar, and the like, may provide health informationassociated with a person. The device data, the biometric data and/orcombination thereof may provide indications whether a person preformsnormal activities (e.g., sleeping, sedentary, or exercising.) or whethera person is having an emergency event (e.g., a person has fallen and/oris experiencing an emergency health event caused by the falling event,and/or a person is having an emergency health event without falling).

In some embodiments, the device data and biometric data used to identifyemergency events may be personalized. For example, thresholds used todetermine when an event has occurred and merits an emergency servicecommunication (e.g., a 9-1-1 call) may be customized based on userprofile settings and/or historical data. A user profile may indicate amedical history, a user habit, a user preference, or the like.Thresholds indicating an occurrence of an emergency event may bedetermined based on a user profile and/or based on data from usershaving similar demographics and/or health profiles. For example,thresholds (e.g., a heart rate threshold, a heart wave threshold, or thelike) indicating whether a person is experiencing a heart attack may beset differently for persons who don't have heart diseases and personswho have heart diseases as indicated in respective user profiles.Thresholds indicating whether a person is experiencing an emergencyevent (e.g., fracture, loss of consciousness, etc.) caused by a fallingevent may be set differently for young persons and seniors who may havean osteoporosis or other health risks. Additionally and/oralternatively, thresholds indicating whether a person is experiencing anemergency event may be adjusted based on activities (e.g., doingworkouts, sleeping, reading, outdoor activities, indoor activities orthe like) of a person over a period of time. For example, if a person isdoing workouts in a gym, the device may adjust the thresholds, such asincreasing a heart rate threshold, a breath rate threshold, a bodytemperature threshold or the like. If a person is sleeping, the devicemay adjust the thresholds, such as reducing a heart rate threshold, abreath rate threshold, a body temperature threshold or the like. In someembodiments, thresholds indicating whether a person is experiencing anemergency event may be adjusted based on surrounding environments (e.g.,temperatures and/or humidity of surrounding environments). For example,if a person moves from a room with air conditioning to an outdoorlocation in summer, the device may adjust the thresholds, such asincreasing a body temperature threshold or the like. In someembodiments, the device may determine thresholds based on historic dataover a predetermined time period, e.g., averaging the historic data, orany other statistical data using the historic data.

In some embodiments, the device may determine an occurrence of anemergency event based on a determination that a change of device dataand/or biometric data deviates from/exceeds/fails to exceed apredetermined threshold. For example, the device may determine currentdata (e.g., current device data and/or biometric data) associated with aperson wearing the device. The device may determine historic data (e.g.,data obtained last time, average data of the historic data over apredetermined time period, or the like) associated with the person. Thedevice may determine one or more thresholds based on the user profilesettings, the historic data, activities associated with the person,surrounding environments, or the like. The device may determine adifference between the current data and historic data. The device maydetermine that an emergency event occurs when the difference deviatesfrom/exceeds/fails to exceed a predetermined threshold.

In some embodiments, the device and/or the remote computing network maygenerate one or more machine learning models to determine an occurrenceof an emergency event. For example, machine learning models may betrained and learn when data merits emergency services. The device maysend device data and/or biometric data captured by sensors to the remotecomputing network concurrently and/or periodically. The remote computingnetwork may train one or more machine learning models using historicdevice data and/or biometric data received from the device such that themachine learning models are able to learn when an emergency eventoccurs. The device may download and store the trained machine learningmodels from the remote computing network concurrently and/orperiodically. The device may use the trained machine learning models toestimate an occurrence of an emergency event based on current and/or newdevice data and/or biometric data obtained from sensors in substantiallyreal-time without sending the current device data and/or biometric datato the remote computing network. For example, when the device isdisconnected with a network (e.g., the device is offline), the devicemay determine an occurrence of an emergency event based on the storedmachine learning models and current device data and/or biometric data.When the device is reconnected with the network (e.g., the device isback online), the device may send the device data and/or biometric dataobtained during the disconnection and update the trained machinelearning models. Accordingly, due to the omission of training themachine learning models, a computing efficiency of the device isimproved. Furthermore, due to the omission of processing on the remotecomputing network, the device may timely (e.g., substantially real-time)to determine an occurrence of an emergency event.

In some embodiments, demographic data may identify when events justifyemergency services based on when users with similar demographic datahave received emergency services. For example, most of seniors may haveosteoporosis problems and/or other health problems. When the seniorshave fallen, the device may determine that the seniors are most likelyto have an emergency event (e.g., fracture, faint, or the like) causedby the falling. When young people have fallen, the device may determinethat the young people are less likely to have an emergency event (e.g.,fracture, faint, or the like) caused by the falling.

In some embodiments, the device may determine an occurrence of anemergency event based on a combination of two or more above methods,e.g., thresholds, machine learning models, and demographic data. Forexample, the device may determine that a person wearing the device hasfallen based on device data by determining that a change of motionand/or location data deviates from/exceeds/fails to exceed apredetermined threshold. The device may utilize machine learning modelsand/or demographic data to determine that the person is most likely tohave an emergency event (e.g., fracture, faint, or the like) caused bythe falling. The device may future determine and/or validate that theperson has fallen based on the determination that biometric data (e.g.,heart rate, breathing rate, pulse oximetry, hydration level, bodytemperature, blood sugar, and the like) associated with the persondeviates from/exceeds/fails to exceed respective predeterminedthresholds.

In some embodiments, the device may determine that a person have fallenand/or is having an emergency health event based on a user input. Anexample user input may include an voice input (e.g., call 911 voicecommand, make a phone call, voice command for asking for help, or thelike), a panic button of the device pressed, or the like. For example,when the device detects an occurrence of an event, the device may send acommunication to another device, which may initiate a communicationsession (e.g., a phone call) with the device, and the person on theother device may request confirmation from the user associated with theevent that the event occurred (e.g., a voice confirmation indicatingthat the person fell, is injured, is having an emergency, etc.). Theconfirmation or lack thereof (e.g., based on the detected event) mayindicate to the other device that the event has occurred, therebyprompting the other device to call an emergency medical professional.When the device detects an event, the device may determine which deviceto contact and in which manner based on the type of event and/or basedon user preferences or device history, and the device may provideinformation to the other device regarding the type of detected event tofacilitate the determination of the proper response (e.g., calling foran ambulance, notifying a medical professional or family member, etc.).

In some embodiments, the device may validate whether a person has fallenbased on one or more communications with user devices associated withthe person and/or a third party (e.g., friends, relatives, nursing whoare close to the person or the like). For example, the device may send aconfirmation request (e.g., an audio request, a message request, a callor the like) to the device or other user devices associated with theperson and/or user devices associated with the third party. The devicemay receive a confirmation (e.g., a voice confirmation, textconfirmation, or the like). In some embodiments, the device may send anotification/alert and associated data (e.g., device data, biometricdata, or the like) to other devices (e.g., a monitoring center, familymembers, etc.). The other devices may contact and/or dispatch medicalprofessionals, ambulance or the like based on the notification/alert andassociated data to provide services for the person who has fallen and/oris having an emergency health event.

In some embodiments, the device may send the associated data (e.g.,device data and biometric data) to the remote computing network torefine machine learning models. In some embodiments, the device may notonly establish a communication between a person wearing the device andthe device, but also establish a communication between the device and auser device (e.g., a mobile phone, smart phone, computer, or the like).For example, a person wearing the device or family members may trackactivities of the person by downloading an application into their userdevices. The device may send device data and biometric data to the userdevices, and the user devices may track and analyze activities of theperson based on received device data and biometric data, e.g.,statistical distribution of the device data and/or biometric data,determining an activity goal for a person, determining whether a personmet an activity goal during a predetermined time period, or the like.

In one or more embodiments, a band of the wearable device may refer to astrap or other mechanism used to hold the device or body of a watch orother wearable device to a user's body (e.g., arm, wrist, etc.).

In one or more embodiments, the wearable device may communicate over oneor more communication channels and spectrums in a time and/or frequencydomain. For example, the wearable device may communicate over cellularcommunication bands, frequency bands (e.g., 700-970 MHz band or anotherband), Wi-Fi, Bluetooth, ultrasound, long-term evolution (LTE), and/orother wireless communications.

In one or more embodiments, the wearable device may communicate withinthe device band and outside of the device band (e.g., using a separatecommunication channel and/or medium).

In one or more embodiments, the power source of the device may becharged wirelessly (e.g., without physically connecting to a powersource). For example, instead of sending wireless data using a wirelessprotocol such as Wi-Fi or Bluetooth, wireless charging may send powerusing wireless signals. Antennas may be used to send signals on behalfof the power source, such as probe request or other type of request tofind nearby power transmitters. The antennas for the power source of thedevice may receive wireless power signals from the nearby power source,and may provide the power signals to the power source of the device tocharge the power source of the device (e.g., a battery).

In one or more embodiments, the device having a display may bedetachable from the watch band. For example, the device may be insertedinto an interior of the band. The band may fully or partially cover adisplay of the device. The band may have material that aresemi-transparent or fully transparent to light emitted from the displaysuch that displayed content may be visible to a user though the band. Insome embodiments, the device may have the same width as the band. Thedevice may have larger or smaller width than the band. In someembodiments, the device may be taken off from the band for charging.

The above descriptions are for purposes of illustration and are notmeant to be limiting. Numerous other examples, configurations,processes, etc., may exist, some of which are described in greaterdetail below. Example embodiments will now be described with referenceto the accompanying figures.

ILLUSTRATIVE PROCESSES AND USE CASES

FIG. 1 illustrates an example system 100 for mobile personal emergencyresponse services using devices, in accordance with one or more exampleembodiments of the present disclosure. As shown in FIG. 1, at step 101,a person 102 may be wearing a watch device 103. At step 104, the person102 may fall, and the watch device 103 may detect the fall (e.g., basedon motion data of the watch device 103 and/or biometric data of theperson 102 detected by the watch device 103). The watch device 103 maydetect the failing event at step 104 based on local analysis of motiondata associated with the watch device 103 (e.g., by comparing the motiondata with one or more thresholds or motion data profiles identified byan event model). Additionally and/or alternatively, the watch device 103may detect an emergency heath event (e.g., with a cardiac event, or thelike) based on local analysis of biometric data associated with theperson 102 by comparing the biometric data (e.g., heart rate data, bloodpressure data, blood glucose data, breathing data, etc., as sensed bythe watch device 103) with one or more thresholds or profiles defined bythe event model. The watch device 103 may initiate a communicationsession (e.g., phone calls using cellar or Wi-Fi, text messages, or thelike) with one or more other devices 108, such as an emergency callcenter device, medical professionals, family members, caregivers, andthe like. The watch device 103 may initiate a phone call from the watchdevice 103 (e.g., using antennae of the watch device 103 rather thanrelying on a paired device to execute the phone call). For example, thewatch device 103 may have cellular and/or Wi-Fi communication capabilityto facilitate phone calls executed using the device (e.g., rather thanrelying on another device, such as a Bluetooth-paired device, to executethe phone call). The one or more other devices 108 may receive thecommunication from the watch device 103, and may respond by sending aquery (e.g., a person or automated system may respond with a voiceutterance 110, such as “Is this an emergency?”) that may be sent to thewatch device 103 and presented to the person 102 to allow the person 102to confirm that an event has occurred. The person 102 may provide a userinput (e.g., voice input, a pressed button input, or the like)indicative of the confirmation to the watch device 103, which mayprovide the confirmation to the one or more other devices 108 (or a lackof response may indicate the occurrence of an event). The one or moreother devices 108 may receive the confirmation and may contact a nearbyemergency center/medical center to dispatch an ambulance 112 or otherpersonnel to a location where the person 102 is (e.g., based on globalpositioning data of the watch device 103), or directly dispatch theambulance 112 to the location. At step 106, a medical professional 107and/or family members may arrive at the location where the person 102 isto provide emergency assistants for the person 102.

In one or more embodiments, the watch device 103 may identify events,such as medical emergencies, based on local (e.g., on-device) analysisof data associated with the person 102. For example, the watch device103 may analyze one or more of device data (e.g., accelerometer or othermotion data) and biometric data (e.g., heart rate data, blood pressuredata, blood glucose data, breathing data, etc.) for the detection of anevent such as fall (e.g., the motion data of the device may indicatethat a person 102 wearing/holding the watch device 103 fell down), acardiac event, or other type of medical emergency. To identify the eventlocally at the watch device 103, the watch device 103 may compare deviceand/or biometric data to a model determined by and received from anotherdevice (e.g., a cloud-based device or other type of device). The modelmay provide criteria, such as data thresholds, data profiles, etc., thatindicate whether device and/or biometric data is indicative of theoccurrence of an event. The watch device 103 may compare device and/orbiometric data to the criteria of the model to determine whether anydetected motion and/or biometric data indicates the occurrence of anevent.

In one or more embodiments, to respond quickly to a detected event, thewatch device 103 may initiate one or more communications, such as phonecalls (e.g., using cellular, Wi-Fi, LTE, etc.), to the one or more otherdevices 108, such as emergency call centers, medical professionals,family members, caregivers, and the like. For example, the watch device103 may have cellular and/or Wi-Fi communication capability tofacilitate phone calls executed using the watch device 103 (e.g., ratherthan relying on another device, such as a Bluetooth-paired device, toexecute the phone call). The watch device 103 may select the one or moreother devices 108 based on preferences of the person 102 and/or the typeof event (e.g., fall, cardiac event, respiratory event, etc.).

The watch device 103 and/or the one or more other devices 108 mayinclude any suitable processor-driven device including, but not limitedto, a mobile device or a non-mobile, e.g., a static, device. Forexample, the watch device 103 and/or the one or more other devices 108may include a user equipment (UE), a station (STA), an access point(AP), a personal computer (PC), a wearable wireless device (e.g.,bracelet, watch, glasses, ring, etc.), a desktop computer, a mobilecomputer, a laptop computer, an Ultrabook™ computer, a notebookcomputer, a tablet computer, a server computer, a handheld computer, ahandheld device, an internet of things (IoT) device, a sensor device, aPDA device, a handheld PDA device, an on-board device, an off-boarddevice, a hybrid device (e.g., combining cellular phone functionalitieswith PDA device functionalities), a consumer device, a vehicular device,a non-vehicular device, a mobile or portable device, a non-mobile ornon-portable device, a mobile phone, a cellular telephone, a PCS device,a PDA device which incorporates a wireless communication device, amobile or portable GPS device, a DVB device, a relatively smallcomputing device, a non-desktop computer, a “carry small live large”(CSLL) device, an ultra mobile device (UMD), an ultra mobile PC (UMPC),a mobile internet device (MID), an “origami” device or computing device,a device that supports dynamically composable computing (DCC), acontext-aware device, a video device, an audio device, an A/V device, aset-top-box (STB), a blu-ray disc (BD) player, a BD recorder, a digitalvideo disc (DVD) player, a high definition (HD) DVD player, a DVDrecorder, a HD DVD recorder, a personal video recorder (PVR), abroadcast HD receiver, a video source, an audio source, a video sink, anaudio sink, a stereo tuner, a broadcast radio receiver, a flat paneldisplay, a personal media player (PMP), a digital video camera (DVC), adigital audio player, a speaker, an audio receiver, an audio amplifier,a gaming device, a data source, a data sink, a digital still camera(DSC), a media player, a smartphone, a television, a music player, orthe like. It is understood that the above is a list of devices. However,other devices, including smart devices, Internet of Things (IoT), suchas lamps, climate control, car components, household components,appliances, etc. may also be included in this list.

FIG. 2 illustrates a block diagram of a wearable device 200 for use inmobile personal emergency response services, in accordance with one ormore example embodiments of the present disclosure.

Referring to FIG. 2, the wearable device 200 (e.g., similar to the watchdevice 103 of FIG. 1) may include a device band 202 and a device body204. The device band 202 may connect to the device body 204, allowingthe wearable device 200 to be worn (e.g., by the person 102 of FIG. 1).The device band 202 (e.g., a watch band or other wearable device band orstrap) may be operatively in communication with the device body 204(e.g., a smart watch device or other mobile device). In someembodiments, the device band 202 may include one or more power sources206 (e.g., batteries) and/or one or more antennae 208 for sendingwireless communications. In some embodiments, the device body 204 mayinclude the one or more power sources 206 or other power sources and/orthe one or more antennae 208. In some embodiments, some componentshaving an intermediate material may be included between the one or morepower sources 206 and the one or more antennae 208. The device band 202may communicate with the device body 204 using a communication bus 210.The device body 204 may include a microphone 212 or other sounddetection device (e.g., capable of voice detection), speakers 214 orother audio/video output device, a system-on-chip 216 or otherprocessing circuitry/hardware, one or more sensors 218 (e.g.,temperature sensors, accelerometers, magnetometers, gyroscopes,biometric sensors, etc.), and one or more transceivers 220 (e.g., tocommunicate wirelessly with other devices and biomedical sensors), oneor more power sources 207 (e.g., batteries), and one or more antennae208. The device body 204 may include memory 211 to store data and/or tostore instructions executable by the system-on-chip 216 or otherprocessing hardware. In some embodiments, the one or more sensors 218may be included in the device band 202 and/or both in the device body204 (e.g., sensors 219).

The wearable device 200 may detect a fall of a user, a voice command(e.g., a “call 911” command, phone call command, text command,reminder/calendar entry command), a wellness anomaly (e.g. a spike inheartrate), a panic button push or touch, and other events. Voicecommands may be sent or translated into text and sent. The wearabledevice 200 may perform the translation or may rely on another device fortranslation. The speakers 214 may play audio alerts or voices (e.g.,voice calls, reminders to take medication, etc.). For example, thewearable device 200 may be capable of two-way communications between thewearable device 200 and other device (e.g., an emergency service phoneor computer). The one or more sensors 218 may detect, using devicelocation (e.g., global navigation satellite system data or morelocalized data using Wi-Fi, Bluetooth, ultrasound, etc.), that thewearable device 200 has passed a geographic boundary (e.g., a geofencing), and the wearable device 200 may send alerts when location,orientation, or biomedical data meet criteria (e.g., exceed or fallbelow threshold values). The alerts may be presented using the wearabledevice 200 and/or may include alerting other devices regarding thestatus of the user or the wearable device 200 (e.g., an alert indicatingthat an event, such as a fall or biomedical event, has occurred). Theone or more sensors 218 may detect motion data and/or biometric datathat the wearable device 200 may analyze to detect the occurrence of anevent (e.g., the falling event of FIG. 1).

In one or more embodiments, having the one or more power sources 206,the one or more antennae 208, and/or the one or more sensors 219 in thedevice band 202, the size of the device body 204 may be reduced and/orthe device body 204 may be used for other hardware.

In one or more embodiments, the one or more power sources 206 and/or theone or more power sources 207 may be chargeable using wireless chargingin which the one or more antennae 208 and/or the one or more antennae209 may receive wireless power signals for the one or more power sources206 and/or the one or more power sources 207. In this manner, the devicebody 204 may be charged by the device band 202 even while a user (e.g.,the person 102 of FIG. 1) is wearing the device body 204 and the deviceband 202 (e.g., in the form of the wearable device 200), or while thewearable device 200 is nearby the user (e.g., on a bedside table whilethe user is sleeping). The one or more antennae 208 and/or the one ormore antennae 209 may request and receive wireless power signals, andthe wireless power signals may be sent to the one or more power sources206 and/or the one or more power sources 207 to charge the one or morepower sources 206 and/or the one or more power sources 207. The one ormore power sources 206 and/or the one or more power sources 207 maysupply power to the one or more antennae 208 and/or the one or moreantennae 209, and to the device body 204.

In one or more embodiments, the one or more sensors 218 may includemotion and position sensors configured to detect device data (e.g.,motion data, location data, or the like), and biometric sensorsconfigured to detect biometric data (e.g., heart rate data, bloodpressure data, blood glucose data, breathing data, etc.). Examples ofmotion and positon sensors may include an accelerometer, a magnetometer,a gyroscope, a proximity sensor, a camera, and any sensors configured todetect motions (e.g., rotations, translations, or the like) and/orpositions associated with a user wearing the wearable device 200.Example of a biometric sensor may include a heart rate sensor, a breathrate sensor, a blood pressure sensor, or any sensor configured tocollect measurable biological characteristics (biometric signals) from auser wearing the wearable device 200.

As shown in FIG. 2, the device body 204 may include databases andmodules 230, such as a model database 232, a sensor data database 234,an event management module 236, a user management module 238, a displaymodule 240, and a communication module 242.

The event management module 236 may perform analysis on data detected bythe one or more sensors 218 and stored in the sensor data database 234to determine an occurrence of an event (e.g., whether a person hasfallen based on accelerometer, magnetometer, and/or gyroscope data,and/or whether the person is having an emergency health event, e.g.,heart attack, blood sugar incident, hyperventilation, or some otherevent). In some embodiments, the event management module 236 maydetermine an occurrence of an emergency event based on a determinationthat a change of device data and/or biometric data deviatesfrom/exceeds/fails to exceed a predetermined threshold. In someembodiments, the predetermined thresholds may be personalized. Forexample, thresholds used to determine when an event has occurred andmerits an emergency service communication (e.g., a 9-1-1 call) may becustomized based on user profile settings and/or historic dataassociated with the sensor data, historic events and associated data. Auser profile generated by the user management module 238 may indicate amedical history, a user habit, a user preference, or the like. Forexample, the event management module 236 may determine current data(e.g., current device data and/or biometric data) associated with aperson wearing the wearable device 200. The event management module 236may determine historic data (e.g., data obtained last time, average dataof the historic data over a predetermined time period, or the like)associated with the person. The event management module 236 maydetermine one or more thresholds based on the user profile settings, thehistoric data, activities associated with the person, surroundingenvironments, or the like. The event management module 236 may determinea difference between the current data and historic data. The device maydetermine that an emergency event occurs when the difference deviatesfrom/exceeds/fails to exceed a predetermined threshold.

In some embodiments, the event management module 236 may generate one ormore machine learning models to determine an occurrence of an emergencyevent. Alternatively, the event management module 236 may customizeevent detection models received from another device (e.g., as explainedfurther with respect to FIG. 3). For example, machine learning modelsmay be trained and learn when data merits emergency services. In someembodiments, the event management module 236 may send device data and/orbiometric data captured by sensors 218 to a remote computing network(e.g., a cloud-based device as shown in FIG. 3) concurrently and/orperiodically. The remote computing network may train one or more machinelearning models using historic device data and/or biometric datareceived from the wearable device 200 such that the machine learningmodels are able to learn when an emergency event occurs. The eventmanagement module 236 may download and store the trained machinelearning models in the model database 232 from the remote computingnetwork concurrently and/or periodically. The event management module236 may use the trained machine learning models to estimate anoccurrence of an emergency event based on current and/or new device dataand/or biometric data obtained from the sensors in substantiallyreal-time without sending the current device data and/or biometric datato the remote computing network. For example, when the wearable device200 is disconnected with a network (e.g., the device is offline), theevent management module 236 may determine an occurrence of an emergencyevent based on the stored machine learning models and current devicedata and/or biometric data. When the wearable device 200 is reconnectedwith the network (e.g., the device is back online), the event managementmodule 236 may send the device data and/or biometric data obtainedduring the disconnection and update the trained machine learning models.

The display module 240 may may generate one or more user interfaces andpresent the user interfaces via a display screen (e.g., as shown inFIGS. 4-6). The size of the screen may be minimized to reduce powerconsumption and to simplify the wearable device 200. The display maypresent the time, date, weather, and information about the user (e.g.,biometric data and/or device).

The communication module 242 may establish communications between a userwearing the wearable device 200 and other devices. In some embodiments,the communication module 242 may initiate a communication session, suchas phone calls (e.g., using cellular or Wi-Fi), to one or more otherdevices, such as emergency call centers, medical professionals, familymembers, caregivers, and the like. For example, the communication module242 may have cellular and/or Wi-Fi communication capability tofacilitate phone calls executed using the wearable device 200 (e.g.,rather than relying on another device, such as a Bluetooth-paireddevice, to execute the phone call). In some embodiments, thecommunication module 242 may receive an user input (e.g., call 911 voicecommand, make a phone call, voice command for asking for help, a panicbutton of the device pressed, or the like) and provide the user input tothe event management module 236 to determine an occurrence of an event.In some embodiments, the communication module 242 may provide a voiceconfirmation indicating that the person fell, is injured, and/or ishaving an emergency in response to a confirmation request from otherdevices. The confirmation or lack thereof (e.g., based on the detectedevent) may indicate to the other device that the event has occurred,thereby prompting the other device to call an emergency medicalprofessional.

The device band 202 and/or the device body 204 may be capable ofexecuting instructions (sequential or otherwise) that specify actions tobe taken by that machine. Further, while only a single machine isillustrated, the term “machine” shall also be taken to include anycollection of machines that individually or jointly execute a set (ormultiple sets) of instructions to perform any one or more of themethodologies discussed herein, such as cloud computing, software as aservice (SaaS), or other computer cluster configurations.

Examples, as described herein, may include or may operate on logic or anumber of components, modules, or mechanisms. Modules are tangibleentities (e.g., hardware) capable of performing specified operationswhen operating. A module includes hardware. In an example, the hardwaremay be specifically configured to carry out a specific operation (e.g.,hardwired). In another example, the hardware may include configurableexecution units (e.g., transistors, circuits, etc.) and a computerreadable medium containing instructions where the instructions configurethe execution units to carry out a specific operation when in operation.The configuring may occur under the direction of the executions units ora loading mechanism. Accordingly, the execution units arecommunicatively coupled to the computer-readable medium when the deviceis operating. In this example, the execution units may be a member ofmore than one module. For example, under operation, the execution unitsmay be configured by a first set of instructions to implement a firstmodule at one point in time and reconfigured by a second set ofinstructions to implement a second module at a second point in time.

A storage device (e.g., the model database 232 and/or the sensor datadatabase 234) of the device band 202 and/or the device body 204 mayinclude a machine readable medium on which is stored one or more sets ofdata structures or instructions (e.g., software) embodying or utilizedby any one or more of the techniques or functions described herein. Theinstructions may also reside, completely or at least partially, within amain memory, within a static memory, or within the hardware processorduring execution thereof by the device band 202 and/or the device body204. In an example, one or any combination of the hardware processor,the main memory, the static memory, or the storage device may constitutemachine-readable media.

The term “machine-readable medium” may include a single medium ormultiple media (e.g., a centralized or distributed database, and/orassociated caches and servers) configured to store one or moreinstructions.

Various embodiments may be implemented fully or partially in softwareand/or firmware. This software and/or firmware may take the form ofinstructions contained in or on a non-transitory computer-readablestorage medium. Those instructions may then be read and executed by oneor more processors to enable performance of the operations describedherein. The instructions may be in any suitable form, such as but notlimited to source code, compiled code, interpreted code, executablecode, static code, dynamic code, and the like. Such a computer-readablemedium may include any tangible non-transitory medium for storinginformation in a form readable by one or more computers, such as but notlimited to read only memory (ROM); random access memory (RAM); magneticdisk storage media; optical storage media; a flash memory, etc.

The term “machine-readable medium” may include any medium that iscapable of storing, encoding, or carrying instructions for execution bythe device band 202 and/or the device body 204 and that cause the deviceband 202 and/or the device body 204 to perform any one or more of thetechniques of the present disclosure, or that is capable of storing,encoding, or carrying data structures used by or associated with suchinstructions. Non-limiting machine-readable medium examples may includesolid-state memories and optical and magnetic media. In an example, amassed machine-readable medium includes a machine-readable medium with aplurality of particles having resting mass. Specific examples of massedmachine-readable media may include non-volatile memory, such assemiconductor memory devices (e.g., electrically programmable read-onlymemory (EPROM), or electrically erasable programmable read-only memory(EEPROM)) and flash memory devices; magnetic disks, such as internalhard disks and removable disks; magneto-optical disks; and CD-ROM andDVD-ROM disks.

Instructions may further be transmitted or received over acommunications network using a transmission medium via the networkinterface device/transceiver utilizing any one of a number of transferprotocols (e.g., frame relay, internet protocol (IP), transmissioncontrol protocol (TCP), user datagram protocol (UDP), hypertext transferprotocol (HTTP), etc.). Example communications networks may include alocal area network (LAN), a wide area network (WAN), a packet datanetwork (e.g., the Internet), mobile telephone networks (e.g., cellularnetworks), plain old telephone (POTS) networks, wireless data networks(e.g., Institute of Electrical and Electronics Engineers (IEEE) 802.11family of standards known as Wi-Fi®, IEEE 802.16 family of standardsknown as WiMax®), IEEE 802.15.4 family of standards, and peer-to-peer(P2P) networks, among others. In an example, the network interfacedevice/transceiver may include one or more physical jacks (e.g.,Ethernet, coaxial, or phone jacks) or one or more antennas to connect toa communications network. In an example, the network interfacedevice/transceiver may include a plurality of antennas to wirelesslycommunicate using at least one of single-input multiple-output (SIMO),multiple-input multiple-output (MIMO), or multiple-input single-output(MISO) techniques. The term “transmission medium” shall be taken toinclude any intangible medium that is capable of storing, encoding, orcarrying instructions for execution by the device band 202 and/or thedevice body 204 and includes digital or analog communications signals orother intangible media to facilitate communication of such software.

FIG. 3 illustrates an example system 300 for enabling emergency responseservices, in accordance with one or more example embodiments of thepresent disclosure.

Referring to FIG. 3, the system 300 may include one or more devices 310(e.g., the wearable device 200 of FIG. 2) in communication with a remotecomputing server 320 (e.g., a cloud-based network with one or moreservers). The remote computing server 320 may be geographically remotefrom the one or more devices 310 (e.g., separate devices in differentphysical/virtual locations).

In one or more embodiments, the one or more devices 310 may include anevent management module 312, a user management module 314, a displaymodule 316, and a commutation module 318. The modules of the one or moredevices 310 may be an embodiment of the event management module 236, theuser management module 238, the display module 240, and thecommunication module 242 in FIG. 2, and may have similar structure andfunctions to the respective modules in FIG. 2. The one or more devices310 may send data 302 to the remote computing server 320. The data 302may include historic and current device data and/or biometric data, oneor more indications of events associated with the above data, or thelike. If the event management module 312 determines an occurrence of anevent, the event management module 312 may initiate one or morecommunications 304 with one or more devices 308 for assistance. Forexample, the one or more communications 304 may include voice calls(e.g., using cellular technology, Wi-Fi, LTE, etc.), messages, and thelike. The one or more communications 304 may identify the type of event(e.g., as defined by the event detection model 330) and/or some of thedata 302 (e.g., to allow the one or more devices 308 and/or users of theone or more devices 308 to identify the possible event and respondappropriately). As referred to herein, the one or more communications304 may be communications sessions, such as cellular or Wi-Fitelecommunications, text message or other message sessions, and the likebetween two or more devices, such as the one or more devices 310 and theone or more devices 308. In this manner, the one or more devices 310 mayinitiate communication sessions with the one or more devices 308 byexecuting operations to place a phone call, send a message, and/orrequest a connection between the devices.

The one or more devices 308 may be devices used by emergency callcenters, medical professionals, family members, caregivers, or the like,such as, but not limited to, mobile, desktop, and/or cloud computingdevices, such as servers. When an emergency notification via the one ormore communications 304 is received by the computing devices 308, theone or more devices 308 may request confirmation (e.g., using the one ormore communications 304) from the person 102 (e.g., a user of the one ormore devices 310) that the detected event occurred (e.g., a voiceconfirmation indicating that the person 102 fell, is injured, is havingan emergency, etc.). The one or more devices 308 may receive aconfirmation (e.g., a voice confirmation, text confirmation, or thelike), using the one or more communications 304, and computing devices308 may contact and/or dispatch medical professionals, ambulance or thelike based on the notification/alert and associated data to provideservices for the person 102 who has fallen and/or is having an emergencyhealth event.

The remote computing server 320 may communicate with the one or moredevices 310 and the one or more devices 308. The remote computing server320 may be one or more remote cloud-based on computers/servers, and/ornetwork-based on computers/servers. The remote computing server 320 mayinclude an event/user management module 322 (optionally), a model module324, and a communication module 326.

In some embodiments, the event/user management module 322 may performsimilar functions to the event management module 236 of FIG. 2. In someembodiments, the event/user management module 322 may track and analyzeactivities of the person 102 based on received device data and biometricdata. The event/user management module 322 may provide inputs and/oroutputs to the one or more devices 308 for presentation and/or futureanalysis via the communication module 326.

The model module 324 may generate one or more event detection models(e.g., machine learning models) configured to identify an occurrence ofan emergency event based on the data 302. For example, machine learningmodels may be trained and learn when data merits emergency services. Themodel module 324 may train one or more machine learning models usinghistoric device data and/or biometric data received from the device 310such that the machine learning models are able to learn when anemergency event occurs. The model module 324 may send an event detectionmodel 330 (e.g., based on the machine learning) to the event managementmodule 312 via the communication module 326. In some embodiments, themodel module 324 may utilize the data 302 to refine the event detectionmodel 330. The event detection model 330 may define the criteria thatthe one or more devices 310 may use to detect an event. The remotecomputing server 320 may send the event detection model 330 to the oneor more devices 310, and may update and send new models to the one ormore devices 310 (e.g., based on feedback received by the one or moredevices 310, such as whether an event detection model properlyidentified an event based on the data 302). For example, the eventdetection model 330 may define data profiles and/or thresholds, such asmotion data profiles that indicate whether a device has moved an amountwithin a certain amount of time, whether biometric data exceeds or failsto exceed biometric thresholds, and the like. In particular, a heartrate above a threshold or below another threshold may indicate anemergency event. A blood glucose level above or below a respectivethreshold may indicate an emergency event. A blood pressure above orbelow a respective threshold may indicate an emergency event. An amountand/or type of device motion may indicate that the person 102 fell. Theevent detection model 330 may account for multiple types of data, timeof day, user inputs, etc. For example, the data 302 may satisfy criteriaindicative of the occurrence of an event, but based on data indicatingthat the person 102 is asleep (e.g., based on heart rate data, breathingdata, etc.), the event detection model 330 may be used by the one ormore devices 310 to determine that an event may not be occurring. Inthis manner, the event detection model 330 may require that multipleconditions are met by multiple types of data to identify the occurrenceof an event.

In one or more embodiments, the one or more devices 310 may communicateusing one or more communications networks 350. The remote computingserver 320 may communicate using one or more communications networks360. The one or more devices 308 may communicate using one or morecommunications networks 370. The one or more communications networks350, the one or more communications networks 360, and/or the one or morecommunications networks 370 may include, but not limited to, any one ofa combination of different types of suitable communications networkssuch as, for example, broadcasting networks, cable networks, publicnetworks (e.g., the Internet), private networks, wireless networks,cellular networks, or any other suitable private and/or public networks.Further, any of the one or more communications networks 350, the one ormore communications networks 360, and/or the one or more communicationsnetworks 370 may have any suitable communication range associatedtherewith and may include, for example, global networks (e.g., theInternet), metropolitan area networks (MANs), wide area networks (WANs),local area networks (LANs), or personal area networks (PANs). Inaddition, any of the one or more communications networks may include anytype of medium over which network traffic may be carried including, butnot limited to, coaxial cable, twisted-pair wire, optical fiber, ahybrid fiber coaxial (HFC) medium, microwave terrestrial transceivers,radio frequency communication mediums, white space communicationmediums, ultra-high frequency communication mediums, satellitecommunication mediums, or any combination thereof.

FIG. 4 illustrates a functional diagram of an exemplary device 400 foruse in mobile personal emergency response services, in accordance withone or more example embodiments of the present disclosure.

Referring to FIG. 4, the device 400 (e.g., similar to the wearabledevice 200 of FIG. 2) may include a device body 410 (e.g., havingfeatures of the device body 204 of FIG. 2) and a device band 420 (e.g.,having features of the device band 202 of FIG. 2). The device band mayhave a battery 422. The battery 422 may be replaced by a battery 424 viaseamless battery swapping without power disengage. The battery 422 maybe removed and placed in contact with or near a charger 426 forcharging. Additionally and/or alternatively, the device 400 may becharged wirelessly via a wireless charger 428. During wireless charging,instead of removing the battery 422 from the device band 420, the entiredevice 400 may be charged without contacting the wireless charger 428.The device body 410 may be further away from the wireless charger 428,but the battery 422 may be closer to the wireless charger 428 withfacing toward the wireless charger 428.

FIG. 5 illustrates a functional diagram of an exemplary device 500 foruse in mobile personal emergency response services, in accordance withone or more example embodiments of the present disclosure.

Referring to FIG. 5, the device 500 (e.g., similar to the wearabledevice 200 of FIG. 2) may include a device body 510 (e.g., havingfeatures of the device body 204 of FIG. 2) and a device band 520 (e.g.,having features of the device band 202 of FIG. 2). The device body 510having a front surface 512 and a back surface 514 may be detachable fromthe device band 520. The device body 510 may be removed from the deviceband 520 and may be placed to contact a charger 530 for charging. Thedevice body 510 may be inserted into a portion of an interior of thedevice band 520. The device band 520 may fully or partially cover adisplay of the device body 510. The device band 520 may have materialthat are semi-transparent or fully transparent to light emitted from thedisplay such that displayed content may be visible to a user though thedevice band 520.

FIG. 6 illustrates a functional diagram of an exemplary device for usein mobile personal emergency response services, in accordance with oneor more example embodiments of the present disclosure.

Referring to FIG. 6, the device 600 (e.g., similar to the wearabledevice 200 of FIG. 2) may include a device body 610 (e.g., havingfeatures of the device body 204 of FIG. 2) and a device band 620 (e.g.,having features of the device band 202 of FIG. 2). The device band 620is a closed band with an opening for containing the device body 610. Thedevice body 610 may be inserted into the opening of the device band 620.A power charger 630 may operatively connect to the device body 610without removing the devices body 610 from the device band 620.

FIG. 7A illustrates an exemplary device 700A for use in mobile personalemergency response services, in accordance with one or more exampleembodiments of the present disclosure.

Referring to FIG. 7A, the device 700A (e.g., similar to the wearabledevice 200 of FIG. 2) may include a device body 710A (e.g., havingfeatures of the device body 204 of FIG. 2) and a device band 720A (e.g.,having features of the device band 202 of FIG. 2). The device band 720Amay include one or more batteries (e.g., the one or more power sources206 of FIG. 2) and one or more antennae (e.g., the one or more antennae208 of FIG. 2). A cross section view 730 of the device band 720A,according to a cross section line 7B-7B, is shown in FIG. 7B.

FIG. 7B illustrates a cross-section 730 of the device band 720A of thedevice 700A of FIG. 7A, in accordance with one or more exampleembodiments of the present disclosure.

Referring to FIG. 7B, one or more layers (e.g., layers associated withan outer surface of the device band 720A) are not shown. The outerlayers of the device band 720A may contain the layers shown in thecross-section 730. As shown, the one or more batteries and the one ormore antennae of the device 700A may be layered within the device band720A, with an antennae layer 732, a first intermediate layer 734 (e.g.,a first shield layer having an intermediate material), a battery layer736 (e.g., the first intermediate layer 734 may be a shield between theantenna layer 732 and the battery layer 736). A second intermediatelayer 738 (e.g., a second shield layer having an intermediate material)may be opposite the first intermediate layer 734 to bookend the batterylayer 736 and protect the battery layer 736. For example, the antennalayer 732 may be an embodiment of the one or more antennae 208 of FIG.2, and the battery layer 736 may be an embodiment of the one or morepower sources 206 of FIG. 2. The intermediate layers may reduceinterference between the antennae layer 732 and the battery layer 736.The antenna layer 732 and the battery layer 736 may be arranged in adifferent order as long as they are separated by an intermediate layer(e.g., as shown in FIG. 7D). The antenna layer 732 may request andreceive power signals to power the battery layer 736, which may powerthe device 700A (e.g., including the device body 710A, such as throughthe communication bus 210 of FIG. 2). The antenna layer 732 may be usedto send wireless communications (e.g., the data 302 of FIG. 3, the oneor more communications 304 of FIG. 3). The antenna layer 732 and thebattery layer 736 may span the entire length of the device band 720A, ormay span respective portions of the device band 720A. Alternatively, theantenna layer 732 and the battery layer 736 may be in separate portionsof the device band 720A. The antenna layer 732 may correspond to the oneor more antennae 208 of FIG. 2, and the battery layer 736 may correspondto the one or more power sources 206 of FIG. 2. The intermediate layersmay be any protective layers and may have insulator properties. Theintermediate layers may have the same or different thicknesses, and/orhave the same or different materials.

FIG. 7C illustrates an exemplary device 700B for use in mobile personalemergency response services, in accordance with one or more exampleembodiments of the present disclosure.

Referring to FIG. 7C, the device 700B (e.g., similar to the wearabledevice 200 of FIG. 2) may include a device body 710B (e.g., havingfeatures of the device body 204 of FIG. 2) and a device band 720B (e.g.,having features of the device band 202 of FIG. 2). The device band 720Bmay include one or more batteries (e.g., the one or more power sources206 of FIG. 2) and one or more antennae (e.g., the one or more antennae208 of FIG. 2). A cross section view 740 of the device band 720B,according to a cross section line 7D-7D, is shown in FIG. 7D.

FIG. 7D illustrates a cross-section 740 of the device band 720B of thedevice 700B of FIG. 7C, in accordance with one or more exampleembodiments of the present disclosure.

Referring to FIG. 7D, the cross-section 740 shows the layers of FIG. 7B,but in a different arrangement. The outer layers of the device band 720Bmay contain the layers shown in the cross-section 740. As shown, thesecond intermediate layer 738 may be arranged on the battery layer 736,which may be arranged on the first intermediate layer 734, which may bearranged on the antenna layer 732. The antenna layer 732 and the batterylayer 736 may span the entire length of the device band 720B, or mayspan respective portions of the device band 720B. Alternatively, theantenna layer 732 and the battery layer 736 may be in separate portionsof the device band 720B. The antenna layer 732 may correspond to the oneor more antennae 208 of FIG. 2, and the battery layer 736 may correspondto the one or more power sources 206 of FIG. 2. The intermediate layersmay be any protective layers and may have insulator properties. Theintermediate layers may have the same or different thicknesses, and/orhave the same or different materials.

It is understood that the above descriptions are for purposes ofillustration and are not meant to be limiting.

FIG. 8 illustrates a flow diagram of an illustrative process 800 forenabling emergency response services, in accordance with one or moreexample embodiments of the present disclosure.

At block 802, a device (e.g., the one or more devices 310 of FIG. 3) mayreceive an event detection model (e.g., the event detection model 330 ofFIG. 3) from a second device (e.g., the remote computing server 320 ofFIG. 3). For example, the device may be a wearable device (e.g., a watchdevice) and may receive a model from a remote computing server (e.g., acloud-based computer/server, or a network-based on computer/server). Themodel may include an event criterion, such as data profiles (e.g.,indicative of certain types of motion, electrocardiographs, etc.),thresholds/ranges respective to different biometric data (e.g., heartrate, blood pressure, blood glucose, respiration, blood oxygen, bodytemperatures, etc.). For example, the model may define thresholds usedto determine when an event has occurred and merits an emergency servicecommunication (e.g., a 9-1-1 call), and the criterion of the model maybe customized based on user profile settings and/or historical data,and/or based on data of users with similar demographics (e.g., age,health profiles, etc.) as permitted and/or authorized by users. In someembodiments, thresholds indicating whether a person is experiencing anemergency event may be adjusted based on activities (e.g., exercising,sleeping, reading, outdoor activities, indoor activities, or the like)of a person over a period of time. In some embodiments, thresholdsindicating whether a person is experiencing an emergency event may beadjusted based on surrounding environments (e.g., temperatures and/orhumidity of surrounding environments). In some embodiments, the remotecomputing server may generate and update one or more machine learningmodels based on data (e.g., device motion data and/or biometric data)received from the wearable device (e.g., the data 302 of FIG. 3), andsend the machine learning models to the wearable device.

At block 804, the device may determine data indicative of an eventassociated with a user. For example, the wearable device may include oneor more sensors (e.g., sensors 218 in FIG. 2) to detect device data(e.g., accelerometer or other motion data) and biometric data (e.g.,heart rate data, blood pressure data, blood glucose data, breathingdata, etc.). The device may provide the data to the second device forgeneration of the event detection model. The device may compare detectedmotion and/or biometric data to the model to identify an event that mayhave occurred.

At block 806, the device may determine, based on a comparison of thedata to the model, an occurrence of the event. For example, the wearabledevice may determine an occurrence of an emergency event based on adetermination that a change of device data and/or biometric datadeviates from/exceeds/fails to exceed a predetermined threshold. Thewearable device may determine current data (e.g., current device dataand/or biometric data) associated with a user wearing the wearabledevice. The wearable device may determine historic data (e.g., dataobtained last time, average data of the historic data over apredetermined time period, or the like) associated with the user. Thewearable device may determine one or more thresholds based on the userprofile settings, the historic data, activities associated with theuser, surrounding environments, or the like. The wearable device maydetermine a difference between the current data and historic data. Thewearable device may determine that an emergency event occurs when thedifference deviates from/exceeds/fails to exceed a predeterminedthreshold. For example, a motion data profile of the model may match themotion data determined at block 804, and may indicate falling event.Biometric data may be compared to criteria specific to the type of data.For example, heart rate data may be compared to one or more heart ratethresholds. Blood pressure data may be compared to one or more bloodpressure thresholds, and so on. Based on device data and/or biometricdata satisfying criteria of the model indicative of an event, the devicemay determine that the data of block 804 indicates that an event mayhave occurred, and the type of event (e.g., based on which type of datasatisfies or matches event criteria defined by the model, which maydefine specific events corresponding to specific event criteria).

At block 808, the device may initiate, based on the occurrence of theevent, a communication session with a third device. For example, thewearable device may initiate one or more communications, such as phonecalls (e.g., using cellular or Wi-Fi), to one or more other devices,such as emergency call centers, medical professionals, family members,caregivers, and the like. For example, the device may have cellularand/or Wi-Fi communication capability to facilitate phone calls executedusing the device (e.g., rather than relying on another device, such as aBluetooth-paired device, to execute the phone call). Thecommunication(s) initiated may be based on the type of event and/or userpreferences. For example, a cardiac event or a falling event may triggera phone call to an emergency service or call center. Some events maytrigger a phone call or message to a caregiver or physician. The typesof communications may be based on user preferences, user contact lists,and the like. The one or more communications may include informationidentifying the event, such as the type of event and/or data used toidentify the event, allowing a receiving party of the one or morecommunications to respond appropriately.

FIG. 9 illustrates a block diagram of an example of a machine 900 (e.g.,the watch device 103 of FIG. 1, the wearable device 200 of FIG. 2, theone or more devices 310 of FIG. 3, the remote computing server 320 ofFIG. 3, the one or more devices 308 of FIG. 4) or system upon which anyone or more of the techniques (e.g., methodologies) discussed herein maybe performed. In other embodiments, the machine 900 may operate as astandalone device or may be connected (e.g., networked) to othermachines. In a networked deployment, the machine 900 may operate in thecapacity of a server machine, a client machine, or both in server-clientnetwork environments. In an example, the machine 900 may act as a peermachine in Wi-Fi direct, peer-to-peer (P2P) (or other distributed)network environments. The machine 900 may be a server, a personalcomputer (PC), a tablet PC, a set-top box (STB), a personal digitalassistant (PDA), a mobile telephone, a wearable computer device, a webappliance, a network router, a switch or bridge, or any machine capableof executing instructions (sequential or otherwise) that specify actionsto be taken by that machine, such as a base station. Further, while onlya single machine is illustrated, the term “machine” shall also be takento include any collection of machines that individually or jointlyexecute a set (or multiple sets) of instructions to perform any one ormore of the methodologies discussed herein, such as cloud computing,software as a service (SaaS), or other computer cluster configurations.

Examples, as described herein, may include or may operate on logic or anumber of components, modules, or mechanisms. Modules are tangibleentities (e.g., hardware) capable of performing specified operationswhen operating. A module includes hardware. In an example, the hardwaremay be specifically configured to carry out a specific operation (e.g.,hardwired). In another example, the hardware may include configurableexecution units (e.g., transistors, circuits, etc.) and a computerreadable medium containing instructions where the instructions configurethe execution units to carry out a specific operation when in operation.The configuring may occur under the direction of the executions units ora loading mechanism. Accordingly, the execution units arecommunicatively coupled to the computer-readable medium when the deviceis operating. In this example, the execution units may be a member ofmore than one module. For example, under operation, the execution unitsmay be configured by a first set of instructions to implement a firstmodule at one point in time and reconfigured by a second set ofinstructions to implement a second module at a second point in time.

The machine (e.g., computer system) 900 may include a hardware processor902 (e.g., a central processing unit (CPU), a graphics processing unit(GPU), a hardware processor core, or any combination thereof), a mainmemory 904 and a static memory 906, some or all of which may communicatewith each other via an interlink (e.g., bus) 908. The machine 900 mayfurther include a power management device 932, a graphics display device910, an alphanumeric input device 912 (e.g., a keyboard), and a userinterface (UI) navigation device 914 (e.g., a mouse). In an example, thegraphics display device 910, alphanumeric input device 912, and UInavigation device 914 may be a touch screen display. The machine 900 mayadditionally include a storage device (i.e., drive unit) 916, a signalgeneration device 918 (e.g., an emitter, a speaker), an event assessmentdevice 919 (e.g., similar to the event management module 312 of FIG. 3and/or to the event/user management module 322 of FIG. 3), a networkinterface device/transceiver 920 coupled to antenna(s) 930, and one ormore sensors 928, such as a global positioning system (GPS) sensor, acompass, an accelerometer, or other sensor. The machine 900 may includean output controller 934, such as a serial (e.g., universal serial bus(USB), parallel, or other wired or wireless (e.g., infrared (IR), nearfield communication (NFC), etc.) connection to communicate with orcontrol one or more peripheral devices (e.g., a printer, a card reader,etc.)).

The storage device 916 may include a machine readable medium 922 onwhich is stored one or more sets of data structures or instructions 924(e.g., software) embodying or utilized by any one or more of thetechniques or functions described herein. The instructions 924 may alsoreside, completely or at least partially, within the main memory 704,within the static memory 906, or within the hardware processor 902during execution thereof by the machine 900. In an example, one or anycombination of the hardware processor 902, the main memory 904, thestatic memory 906, or the storage device 916 may constitutemachine-readable media.

The event assessment device 919 may carry out or perform any of theoperations and processes (e.g., process 800 of FIG. 8) described above.The event assessment device 919 may be included in the wearable device200 of FIG. 2.

While the machine-readable medium 922 is illustrated as a single medium,the term “machine-readable medium” may include a single medium ormultiple media (e.g., a centralized or distributed database, and/orassociated caches and servers) configured to store the one or moreinstructions 924.

Various embodiments may be implemented fully or partially in softwareand/or firmware. This software and/or firmware may take the form ofinstructions contained in or on a non-transitory computer-readablestorage medium. Those instructions may then be read and executed by oneor more processors to enable performance of the operations describedherein. The instructions may be in any suitable form, such as but notlimited to source code, compiled code, interpreted code, executablecode, static code, dynamic code, and the like. Such a computer-readablemedium may include any tangible non-transitory medium for storinginformation in a form readable by one or more computers, such as but notlimited to read only memory (ROM); random access memory (RAM); magneticdisk storage media; optical storage media; a flash memory, etc.

The term “machine-readable medium” may include any medium that iscapable of storing, encoding, or carrying instructions for execution bythe machine 900 and that cause the machine 900 to perform any one ormore of the techniques of the present disclosure, or that is capable ofstoring, encoding, or carrying data structures used by or associatedwith such instructions. Non-limiting machine-readable medium examplesmay include solid-state memories and optical and magnetic media. In anexample, a massed machine-readable medium includes a machine-readablemedium with a plurality of particles having resting mass. Specificexamples of massed machine-readable media may include non-volatilememory, such as semiconductor memory devices (e.g., electricallyprogrammable read-only memory (EPROM), or electrically erasableprogrammable read-only memory (EEPROM)) and flash memory devices;magnetic disks, such as internal hard disks and removable disks;magneto-optical disks; and CD-ROM and DVD-ROM disks.

The instructions 924 may further be transmitted or received over acommunications network 926 using a transmission medium via the networkinterface device/transceiver 920 utilizing any one of a number oftransfer protocols (e.g., frame relay, internet protocol (IP),transmission control protocol (TCP), user datagram protocol (UDP),hypertext transfer protocol (HTTP), etc.). Example communicationsnetworks may include a local area network (LAN), a wide area network(WAN), a packet data network (e.g., the Internet), mobile telephonenetworks (e.g., cellular networks), plain old telephone (POTS) networks,wireless data networks (e.g., Institute of Electrical and ElectronicsEngineers (IEEE) 802.11 family of standards known as Wi-Fi®, IEEE 802.16family of standards known as WiMax®), IEEE 802.15.4 family of standards,and peer-to-peer (P2P) networks, among others. In an example, thenetwork interface device/transceiver 920 may include one or morephysical jacks (e.g., Ethernet, coaxial, or phone jacks) or one or moreantennas to connect to the communications network 926. In an example,the network interface device/transceiver 920 may include a plurality ofantennas to wirelessly communicate using at least one of single-inputmultiple-output (SIMO), multiple-input multiple-output (MIMO), ormultiple-input single-output (MISO) techniques. The term “transmissionmedium” shall be taken to include any intangible medium that is capableof storing, encoding, or carrying instructions for execution by themachine 900 and includes digital or analog communications signals orother intangible media to facilitate communication of such software.

The operations and processes described and shown above may be carriedout or performed in any suitable order as desired in variousimplementations. Additionally, in certain implementations, at least aportion of the operations may be carried out in parallel. Furthermore,in certain implementations, less than or more than the operationsdescribed may be performed.

The word “exemplary” is used herein to mean “serving as an example,instance, or illustration.” Any embodiment described herein as“exemplary” is not necessarily to be construed as preferred oradvantageous over other embodiments. The terms “computing device,” “userdevice,” “communication station,” “station,” “handheld device,” “mobiledevice,” “wireless device” and “user equipment” (UE) as used hereinrefers to a wireless communication device such as a cellular telephone,a smartphone, a tablet, a netbook, a wireless terminal, a laptopcomputer, a femtocell, a high data rate (HDR) subscriber station, anaccess point, a printer, a point of sale device, an access terminal, orother personal communication system (PCS) device. The device may beeither mobile or stationary.

As used within this document, the term “communicate” is intended toinclude transmitting, or receiving, or both transmitting and receiving.This may be particularly useful in claims when describing theorganization of data that is being transmitted by one device andreceived by another, but only the functionality of one of those devicesis required to infringe the claim. Similarly, the bidirectional exchangeof data between two devices (both devices transmit and receive duringthe exchange) may be described as “communicating,” when only thefunctionality of one of those devices is being claimed. The term“communicating” as used herein with respect to a wireless communicationsignal includes transmitting the wireless communication signal and/orreceiving the wireless communication signal. For example, a wirelesscommunication unit, which is capable of communicating a wirelesscommunication signal, may include a wireless transmitter to transmit thewireless communication signal to at least one other wirelesscommunication unit, and/or a wireless communication receiver to receivethe wireless communication signal from at least one other wirelesscommunication unit.

As used herein, unless otherwise specified, the use of the ordinaladjectives “first,” “second,” “third,” etc., to describe a commonobject, merely indicates that different instances of like objects arebeing referred to and are not intended to imply that the objects sodescribed must be in a given sequence, either temporally, spatially, inranking, or in any other manner.

Some embodiments may be used in conjunction with various devices andsystems, for example, a personal computer (PC), a desktop computer, amobile computer, a laptop computer, a notebook computer, a tabletcomputer, a server computer, a handheld computer, a handheld device, apersonal digital assistant (PDA) device, a handheld PDA device, anon-board device, an off-board device, a hybrid device, a vehiculardevice, a non-vehicular device, a mobile or portable device, a consumerdevice, a non-mobile or non-portable device, a wireless communicationstation, a wireless communication device, a wireless access point (AP),a wired or wireless router, a wired or wireless modem, a video device,an audio device, an audio-video (A/V) device, a wired or wirelessnetwork, a wireless area network, a wireless video area network (WVAN),a local area network (LAN), a wireless LAN (WLAN), a personal areanetwork (PAN), a wireless PAN (WPAN), and the like.

Some embodiments may be used in conjunction with one way and/or two-wayradio communication systems, cellular radio-telephone communicationsystems, a mobile phone, a cellular telephone, a wireless telephone, apersonal communication system (PCS) device, a PDA device whichincorporates a wireless communication device, a mobile or portableglobal positioning system (GPS) device, a device which incorporates aGPS receiver or transceiver or chip, a device which incorporates an RFIDelement or chip, a multiple input multiple output (MIMO) transceiver ordevice, a single input multiple output (SIMO) transceiver or device, amultiple input single output (MISO) transceiver or device, a devicehaving one or more internal antennas and/or external antennas, digitalvideo broadcast (DVB) devices or systems, multi-standard radio devicesor systems, a wired or wireless handheld device, e.g., a smartphone, awireless application protocol (WAP) device, or the like.

Some embodiments may be used in conjunction with one or more types ofwireless communication signals and/or systems following one or morewireless communication protocols, for example, radio frequency (RF),infrared (IR), frequency-division multiplexing (FDM), orthogonal FDM(OFDM), time-division multiplexing (TDM), time-division multiple access(TDMA), extended TDMA (E-TDMA), general packet radio service (GPRS),extended GPRS, code-division multiple access (CDMA), wideband CDMA(WCDMA), CDMA 2000, single-carrier CDMA, multi-carrier CDMA,multi-carrier modulation (MDM), discrete multi-tone (DMT), Bluetooth®,global positioning system (GPS), Wi-Fi, Wi-Max, ZigBee, ultra-wideband(UWB), global system for mobile communications (GSM), 2G, 2.5G, 3G,3.5G, 4G, fifth generation (5G) mobile networks, 3GPP, long termevolution (LTE), LTE advanced, enhanced data rates for GSM Evolution(EDGE), or the like. Other embodiments may be used in various otherdevices, systems, and/or networks.

It is understood that the above descriptions are for purposes ofillustration and are not meant to be limiting.

Although specific embodiments of the disclosure have been described,numerous other modifications and alternative embodiments are within thescope of the disclosure. For example, any of the functionality describedwith respect to a particular device or component may be performed byanother device or component. Further, while specific devicecharacteristics have been described, embodiments of the disclosure mayrelate to numerous other device characteristics. Further, althoughembodiments have been described in language specific to structuralfeatures and/or methodological acts, it is to be understood that thedisclosure is not necessarily limited to the specific features or actsdescribed. Rather, the specific features and acts are disclosed asillustrative forms of implementing the embodiments. Conditionallanguage, such as, among others, “can,” “could,” “might,” or “may,”unless specifically stated otherwise, or otherwise understood within thecontext as used, is generally intended to convey that certainembodiments could include, while other embodiments may not include,certain features, elements, and/or steps. Thus, such conditionallanguage is not generally intended to imply that features, elements,and/or steps are in any way required for one or more embodiments.

What is claimed is:
 1. A method, comprising: receiving, by at least one processor of a first device, a model from a second device, the model comprising an event criterion, wherein the first device is a wearable device; determining, by the at least one processor, data indicative of an event associated with a user; determining, by the at least one processor, based on a comparison of the data to the model, an occurrence of the event; and initiating, by the at least one processor, based on the occurrence of the event, a communication session with a third device.
 2. The method of claim 1, wherein the data is first data, the event is a first event, wherein the model is a first model, wherein the event criterion is a first event criterion, and wherein the communication session is a first communication session, the method further comprising: sending the first data and an indication of the first event to the second device; receiving a second model from the second device, wherein the second model comprises a second event criterion different than the first event criterion, and wherein the second event criterion are based on the first data and the indication of the first event; determining second data indicative of a second event associated with the user; determining, based on a comparison of the second data to the second model, an occurrence of the second event; and initiating, based on the occurrence of the second event, a second communication session.
 3. The method of claim 1, further comprising: determining, based on the data and the model, an event type associated with the event; and sending an indication of the event type to the third device.
 4. The method of claim 1, wherein the event is associated with a user falling, and wherein the data comprises motion data associated with one or more accelerometers of the first device.
 5. The method of claim 1, wherein the event is associated with a cardiac event, and wherein the data comprises biometric data associated with a user wearing the first device.
 6. The method of claim 1, wherein the event criterion comprises one or more thresholds based on at least one of a user profile associated with a user wearing the first device, activities performed by the user over a period of time, a surrounding environment associated with the first device, or historic data associated with the user.
 7. The method of claim 1, further comprising: receiving, from the third device, a query associated with confirming the occurrence of the event; receiving a user input indicative of the confirmation; and sending, to the third device, an indication of the confirmation.
 8. The method of claim 1, wherein the first device comprises a wearable band, the wearable band comprising a power source, the method further comprising receiving power from the power source.
 9. The method of claim 8, wherein the wearable band further comprises an antenna, wherein the communication session is initiated using the antenna.
 10. The method of claim 9, wherein the wearable band further comprises an intermediate material between the antenna and the power source.
 11. The method of claim 1, further comprising: determining a user preference associated with the event and the third device, wherein initiating the communication session with the third device is based on the user preference.
 12. The method of claim 1, further comprising: determining, based on the model, that the event is associated with an event type, wherein initiating the communication session with the third device is based on the event type.
 13. The method of claim 1, wherein the communication session is a first communication session, the method further comprising: initiating a second communication session with a fourth device based on the occurrence of the event.
 14. A wearable apparatus comprising: a band comprising a power source; and processing circuitry coupled to the power source and to memory, the processing circuitry configured to: receive, from a first device, a model comprising event criteria; determine data indicative of an event associated with a user; determine, based on a comparison of the data to the model, an occurrence of the event; and initiating, based on the occurrence of the event, a communication session with a second device.
 15. The wearable apparatus of claim 14, wherein the wearable apparatus is geographically remote from the first device.
 16. The wearable apparatus of claim 14, wherein the communication session comprises a cellular telecommunication.
 17. The wearable apparatus of claim 14, wherein the band further comprises an antenna.
 18. A system, comprising: a band comprising a power source; and processing circuitry coupled to the power source and to memory, the processing circuitry configured to: receive, from a first device, a model comprising event criteria; determine data indicative of an event associated with a user; determine, based on a comparison of the data to the model, an occurrence of the event; and initiating, based on the occurrence of the event, a communication session with a second device.
 19. The system of claim 18, wherein the system is geographically remote from the first device.
 20. The system of claim 18, wherein the band further comprises an antenna. 